Automatic soil and stone material grading detection method based on image optimization classification

Abstract

The invention discloses an automatic soil and stone material grading detection method based on image optimization classification. The method comprises the steps that grade-mixed soil and stone material images acquired under different illumination conditions are processed by adopting gamma transform processing, and the images under various bright and dark illumination conditions are adaptively processed; the soil and stone material images are processed through an adaptive threshold method by adopting a dynamic otsu optimization technology, and soil targets and stone targets are distinguished; density transform is conducted on binary images, complete stone materail areas are retained, and the noise influences of soil and stone parts are weakened; morphological transform is conducted on the binary images, ore edge information weakened in the density transform process is enhanced, and ore target boundaries in the images are extracted and subjected to geographical morphology statistics; andthe targets in the images are subjected to pseudo target removal, the retained ore targets are subjected to grade, size and mass calculation, and accumulated grading curve distribution of the soil and stone material is acquired. The method is suitable for automatic detection of the different grades-mixed soil and stone material and further suitable for automatic detection of various stone grades.

Description

technical field [0001] The invention relates to a detection technology of soil-rock gradation obtained by mixing stones of different particle sizes and different materials with sand and soil, in particular to an automatic detection method of soil-rock gradation based on image optimization classification. Background technique [0002] Soil and stone materials are mixed with stones of different sizes and sand, and are used for concrete building construction, earth-rock roadbed construction, bridges and water conservancy dams. The particle size distribution detection of earth and rock materials can improve the material use efficiency of earth and rock materials, speed up the construction speed of the above-mentioned construction process and enhance the firmness of the construction target, which is of great significance to the above-mentioned engineering construction. Among the soil and rock materials at the construction site, the soil and rock materials are different, and the p...

AI Technical Summary

Problems solved by technology

[0004] At present, the particle size of soil and rock materials is mainly obtained through manual screening, which is time-consuming and laborious, and the efficiency is very low

There are very few methods in the prior art that can automatically analyze the particle size of soil and rock

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